Least squares learning and the US Treasury bill rate

Understanding how agents formulate their expectations about Fed behavior is important for market participants because they can potentially use this information to make more accurate estimates of stock and bond prices. Although it is commonly assumed that agents learn over time, there is scant empirical evidence in support of this assumption. Thus, in this paper we test if the forecast of the three month T-bill rate in the Survey of Professional Forecasters (SPF) is consistent with least squares learning when there are discrete shifts in monetary policy. We first derive the mean, variance and autocovariances of the forecast errors from a recursive least squares learning algorithm when there are breaks in the structure of the model. We then apply the Bai and Perron (1998) test for structural change to a forecasting model for the three month T-bill rate in order to identify changes in monetary policy. Having identified the policy regimes, we then estimate the implied biases in the interest rate forecasts within each regime. We find that when the forecast errors from the SPF are corrected for the biases due to shifts in policy, the forecasts are consistent with least squares learning. © 2014 Elsevier B.V.

Corrigendum to “Least squares learning and the US treasury bill rate” [Econ. Syst. 38 (2014) 194–204]

Understanding how agents formulate their expectations about Fed behavior is important for market participants because they can potentially use this information to make more accurate estimates of stock and bond prices. Although it is commonly assumed that agents learn over time, there is scant empirical evidence in support of this assumption. Thus, in this paper we test if the forecast of the three month T-bill rate in the Survey of Professional Forecasters (SPF) is consistent with least squares learning when there are discrete shifts in monetary policy. We first derive the mean, variance and autocovariances of the forecast errors from a recursive least squares learning algorithm when there are breaks in the structure of the model. We then apply the Bai and Perron (1998) test for structural change to a forecasting model for the three month T-bill rate in order to identify changes in monetary policy. Having identified the policy regimes, we then estimate the implied biases in the interest rate forecasts within each regime. We find that when the forecast errors from the SPF are corrected for the biases due to shifts in policy, the forecasts are consistent with least squares learning.

Does monetary policy matter in a less developed economy? Evidence from Bangladesh

This paper explores the role of monetary policy in the context of a less developed economy. Monetary transmission mechanisms in less developed economies can be quite different from an industrialized economy, as unlike industrialized countries, these economies are characterized by the small size of organized financial markets, limited substitutability between money and other assets and weak fiscal and monetary institutions. We utilize the Structural VAR approach to analyze the monetary transmission process and impacts of monetary policy on different macro variables in Bangladesh. Monetary policy shocks are identified using non-recursive contemporaneous restrictions, which are based on the Central Bank's reaction function and the structure of the economy. We found strong evidence for the interest rate channel of monetary policy in Bangladesh. Our findings indicate that monetary policy shocks are important sources of fluctuations in the rate of interest, output and prices. Expansionary monetary policies are found to be harmful for achieving price stability in Bangladesh, as they not only increase the prices permanently, but also make the price level more volatile. We also found the evidence of a long lasting effect of monetary policy on output, which suggests that contractionary policy measures may create sustained recession in Bangladesh.

An analysis of Fiji's monetary policy transmission

Purpose – The purpose of this paper is to examine the monetary policy transmission mechanism for the Fiji Islands using a structural vector autoregressive (SVAR) model for the period 1975 to 2005.

Design/methodology/approach – The SVAR model investigates how a monetary policy shock – defined as a temporary and exogenous rise in the short-term interest rate – affects real and nominal macro variables; namely real output, prices, exchange rates, and money supply.

Findings – The results suggest that a monetary policy shock statistically significantly reduces output initially, but then output is able to recover to its pre-shock level. A monetary policy shock generates inflationary pressure, leads to an appreciation of the Fijian currency and reduces the demand for money. The paper also analysed the impact of a nominal effective exchange rate (NEER) shock (an appreciation) on real output and found that it leads to a statistically significant negative effect on real output.

Practical implications – The findings of this study should be of direct relevance to the research and policy work undertaken at the Reserve Bank of Fiji.

Originality/value – For a small economy, such as Fiji, where monetary policy is key to sustainable macroeconomic management, this is the first paper that undertakes a dynamic analysis of monetary policy transmission. The paper uses time series data over three decades and builds a structural VAR model, rooted in theory. This paper will be of direct relevance to the Reserve Bank of Fiji. The approach and model proposed will also be useful for applied monetary policy researchers in other developing countries where inflation rate targeting is a key element of the monetary policy setting.

Has the structural break slowed down growth rates of stock markets?

In this paper, we use the common structural break test suggested by Bai et al. (1998) to test for a common structural break in the stock prices of the US, the UK, and Japan. On the basis of the structural break, we divide each country's stock price series into sub-samples and investigate whether or not the structural break had slowed down the growth of stock markets. Our main findings are that when stock markets are modelled in a trivariate sense the common structural break turns out to be 1990:02, with the confidence interval including several episodes, such as the asset price bubble when housing prices and stock prices in Japan reached a peak in 1988/1989, the early 1990s recession in the UK, the business cycle peak of July 1990, the August 1990 Iraqi invasion of Kuwait and the March 1991 business cycle trough. Annual average growth rates suggest that the structural break has slowed down the growth rate of the US, the UK and Japanese stock markets.

Investigating the housing market fluctuation under an expansionary monetary policy in Australia

This research empirically investigates the impact of monetary policy on the housing market in Australia from 1996 to 2009. Three primary variables associated with the housing sector and monetary policy, including interest rates, money supply and house prices, are estimated by a structural vector autoregression (VAR) model. Depending upon the analysis using the impulse response function, it can be identified that monetary policy significantly affects the housing market in Australia by the adjustments in interest rates and money supply. The empirical results from this study may be useful for policy makers to enact appropriate policies in relation to the infrastructure planning.

The structure of tourist expenditure in Fiji : evidence from unit root structural break tests

The central aim of this paper is to investigate whether shocks to Fiji's tourism industry have a permanent effect or a transitory effect on tourist expenditure in Fiji. To accomplish this aim the Zivot and Andrews (1992) one break test and the Lumsdaine and Papell (1997) two break tests are used. The one break and two break tests reveal 1987 - the year of the military coups in Fiji - as the year of the break. Moreover, it is possible to reject the unit root null leading to the conclusion that shocks to Fiji's tourism industry have a transitory effect on tourist expenditure in Fiji.

Analysing the transmission pattern within the framework of housing supply and monetary policy in Australia

Housing supply is one of important components of the housing sector. Compared with an increasingly strong housing demand, the growth rates of total housing stock in Australia have exhibited a downward trend since the end of the 1990s whilst the significant adjustments in the Australian monetary policy were being implemented. This research aims to estimate the nature of the relationship between housing supply and monetary policy by a vector error correction model. According to the empirical results, a transmission pattern comprised of the indicators associated with housing supply and monetary policy can be identified, which suggests that there is a significant interrelationship between monetary policy and the supply side of the housing sector in Australia.

Terms of trade shocks and monetary policy in India

Central banks in emerging market economies often grapple with understanding the monetary policy response to an inter-sectoral terms of trade shock. To address this, we develop a three sector closed economy NK-DSGE model calibrated to India. Our framework can be generalized to other emerging markets and developing economies. The model is characterized by a manufacturing sector and an agricultural sector. The agricultural sector is disaggregated into a grain and vegetable sector. The government procures grain from the grain market and stores it. We show that the procurement of grain leads to higher inflation, a change in the sectoral terms of trade, and a positive output gap because of a change in the sectoral allocation of labor. We compare the transmission of a single period positive procurement shock with a single period negative productivity shock and discuss the implications of such shocks for monetary policy setting. Our paper contributes to a growing literature on monetary policy in India and other emerging market economies.

Revisiting the US money demand function: an application of the Lagrange multiplier structural break unit root test and the bounds test for a long-run relationship

In this article, we examine the issue of a levels relationship and stability of the US money demand function over the period 1959:01 to 2004:02. We use the Lagrange multiplier structural break unit root test and the bounds testing approach to a long-run relationship in levels of the variables, namely real money demand, nominal interest rate and real income. We find greater evidence for a long-run relationship in levels and stability of the US money demand function when we use M2 as a proxy for money demand. However, we find little evidence for a long-run relationship between M1 and M2 with their determinants for the recent period, spanning the last decade or so.